Interactive Image Segmentation via Adaptive Weighted Distances Export

@article{citeulike:2086350, abstract = {An interactive algorithm for soft segmentation of natural images is presented in this paper. The user first roughly scribbles different regions of interest, and from them, the whole image is automatically segmented. This soft segmentation is obtained via fast, linear complexity computation of weighted distances to the user-provided scribbles. The adaptive weights are obtained from a series of Gabor filters, and are automatically computed according to the ability of each single filter to discriminate between the selected regions of interest. We present the underlying framework and examples showing the capability of the algorithm to segment diverse images}, author = {Protiere, A. and Sapiro, G.}, booktitle = {Image Processing, IEEE Transactions on}, citeulike-article-id = {2086350}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/TIP.2007.891796}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4130436}, doi = {10.1109/TIP.2007.891796}, journal = {Image Processing, IEEE Transactions on}, keywords = {distance, geodesic, interactive, scribbles, segmentation}, number = {4}, pages = {1046--1057}, posted-at = {2007-12-10 17:46:10}, priority = {5}, title = {Interactive Image Segmentation via Adaptive Weighted Distances}, url = {http://dx.doi.org/10.1109/TIP.2007.891796}, volume = {16}, year = {2007} }

TY - JOUR ID - citeulike:2086350 L3 - citeulike-article-id:2086350 N2 - An interactive algorithm for soft segmentation of natural images is presented in this paper. The user first roughly scribbles different regions of interest, and from them, the whole image is automatically segmented. This soft segmentation is obtained via fast, linear complexity computation of weighted distances to the user-provided scribbles. The adaptive weights are obtained from a series of Gabor filters, and are automatically computed according to the ability of each single filter to discriminate between the selected regions of interest. We present the underlying framework and examples showing the capability of the algorithm to segment diverse images IS - 4 JF - Image Processing, IEEE Transactions on EP - 1057 TI - Interactive Image Segmentation via Adaptive Weighted Distances VL - 16 T2 - Image Processing, IEEE Transactions on SP - 1046 KW - distance KW - geodesic KW - interactive KW - scribbles KW - segmentation AU - Protiere, A AU - Sapiro, G PY - 2007/// UR - http://dx.doi.org/10.1109/TIP.2007.891796 ER -